hesim 0.1.0.9000

The current development version of hesim.

Highlights

hesim now provides a general framework for integrating statistical models with economic evaluation. Users can build a decision model by specifying a model structure, which consists of a set of statistical models for disease progression, utility values, and costs. Each statistical model is used to simulate outcomes as a function of estimated parameters. N-state partitioned survival models (PSMs) and individual-level continuous time state transition models (CTSTMs) are now supported.

API changes

• The argument sim was renamed sample in icea(), icea_pw(), and incr_effect().
• Custom functions and variables are no longer supported in icea and icea_pw().

New features

Fitted statistical models

• There are functions to create objects that store collections of fitted statistical models or formula objects. These include partsurvfit(), formula_list(), and flexsurvreg_list().

Parameters

• Functions prefixed by params_ create objects storing samples of parameters of fitted statistical models for probabilistic sensitivity analysis.
• create_params() is a generic function for creating parameter objects from a fitted statistical model or a formula object. Parameters can be sampled using Monte Carlo multivariate normal approximations or via bootstrapping.
• Current support for flexible survival modeling (params_surv(), params_surv_list()) and linear regression (params_lm()). Splines and parametric distributions (exponential, Weibull, Gompertz, gamma, lognormal log-logistic, generalized gamma) are supported for survival modeling.

Input data

• hesim_data() creates an object of class hesim_data for storing a collection of data tables or data frames for simulation modeling.
• expand.hesim_data() combines some or all of the data tables or data frames in hesim_data() into a single long dataset.
• input_data() creates an object of class input_data, which contains data for predicting or simulating values with a statistical model.
• create_input_data() creates an object of class input_data from a fitted statistical model or a formula object.

Health state values

• The R6 class StateVals simulates the costs or utilities associated with health states.
• create_StateVals() creates a StateVals object from fitted statistical models or formula objects.

Partitioned survival models

• The R6 class Psm simulates outcomes from N-state PSMs.
• A Psm object is instantiated with a set of survival models (the R6 class PsmCurves) and models for costs and utility (the R6 class StateVals).
• create_PsmCurves() creates a PsmCurves object from fitted statistical models or formula objects.

Continuous time state transition models

• The R6 class IndivCtstm simulates individual-level CTSTMs. Semi-Markov (i.e., “clock reset”) models are currently supported.
• A IndivCtstm object is instantiated with a health state transition model (the R6 class CtstmTrans) and models for costs and utility (the R6 class StateVals).
• create_CtstmTrans() creates a CtstmTrans object from fitted statistical models or formula objects.

Datasets

• psm4_exdata provides example datasets for parameterizing a PSM.
• ctstm3_exdata provides example datasets for parameterizing a CTSTM.

hesim 0.1.0

The initial CRAN submission.